---
library_name: transformers
license: apache-2.0
base_model: google/mobilebert-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: xdefender-edge-sms
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# xdefender-edge-sms

This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 137548.8125
- Accuracy: 0.6154
- Precision: 0.6154
- Recall: 1.0
- F1: 0.7619

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 13
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2062021.6     | 1.0   | 13   | 850877.375      | 0.3846   | 0.0       | 0.0    | 0.0    |
| 660729.65     | 2.0   | 26   | 150588.2344     | 0.6154   | 0.6154    | 1.0    | 0.7619 |
| 111387.95     | 3.0   | 39   | 4234.5283       | 0.5385   | 0.6429    | 0.5625 | 0.6    |
| 5760.7262     | 4.0   | 52   | 2093.7539       | 0.4231   | 1.0       | 0.0625 | 0.1176 |
| 2538.1734     | 5.0   | 65   | 202.3052        | 0.3077   | 0.0       | 0.0    | 0.0    |
| 1129.3242     | 6.0   | 78   | 91.8728         | 0.6154   | 0.6154    | 1.0    | 0.7619 |
| 205.6373      | 7.0   | 91   | 15.5296         | 0.3846   | 0.0       | 0.0    | 0.0    |
| 30.6633       | 8.0   | 104  | 3.3818          | 0.6154   | 0.6154    | 1.0    | 0.7619 |
| 3.7607        | 9.0   | 117  | 1.7103          | 0.3846   | 0.0       | 0.0    | 0.0    |
| 1.1705        | 10.0  | 130  | 0.7337          | 0.4615   | 1.0       | 0.125  | 0.2222 |


### Framework versions

- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.1
- Tokenizers 0.23.1